An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics

For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types

“The Times They Are A-Changin’” at Diabetes Care

Every five years or so, the editorial team leading Diabetes Care turns over with the appointment of new leadership. This issue of volume 46 represents the first of a new editorial team, making it the tenth group to be responsible for the scientific content of the journal. Starting in 1978 with Jay Skyler as its first editor, Diabetes Care has gone from strength to strength with new initiatives and a steady increase in its influence. This impact has been in line with the charge given at the journal’s founding by the then president of the American Diabetes Association Norbert Freinkel when he wrote, “The new journal is designed to promote better patient care by serving the expanded needs of all health professionals committed to the care of patients with diabetes.

Driver Fusions and Their Implications in the Development and Treatment of Human Cancers.

Gene fusions represent an important class of somatic alterations in cancer. We systematically investigated fusions in 9,624 tumors across 33 cancer types using multiple fusion calling tools. We identified a total of 25,664 fusions, with a 63% validation rate. Integration of gene expression, copy number, and fusion annotation data revealed that fusions involving oncogenes tend to exhibit increased expression, whereas fusions involving tumor suppressors have the opposite effect. For fusions involving kinases, we found 1,275 with an intact kinase domain, the proportion of which varied significantly across cancer types. Our study suggests that fusions drive the development of 16.5% of cancer cases and function as the sole driver in more than 1% of them. Finally, we identified druggable fusions involving genes such as TMPRSS2, RET, FGFR3, ALK, and ESR1 in 6.0% of cases, and we predicted immunogenic peptides, suggesting that fusions may provide leads for targeted drug and immune therapy

Search for leptophobic Z ' bosons decaying into four-lepton final states in proton-proton collisions at root s=8 TeV

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Search for black holes and other new phenomena in high-multiplicity final states in proton-proton collisions at root s=13 TeV

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Search for heavy resonances decaying into a vector boson and a Higgs boson in final states with charged leptons, neutrinos, and b quarks

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Search for high-mass diphoton resonances in proton-proton collisions at 13 TeV and combination with 8 TeV search

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Measurements of differential production cross sections for a Z boson in association with jets in pp collisions at root s=8 TeV

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Measurements of t(t)over-bar charge asymmetry using dilepton final states in pp collisions at root s=8 TeV

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